Effects of Thermal Modifications on the Rheological Characteristics and Protein Quality of Three Species of Fish of Varying Collagen Content

School of Industrial Fisheries, Cochin University of Science and Technology

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

Studies On The Dynamics And Water Quality Of The Muvattupuzha River In Relation To Effluent Discharge

The present study aims at the investigation of the 1ysico—chemical features of a tropical tidal river viz. we Muvattupuzha river. This river is expected to receive Jderate to heavy pollution loads in years to come, from we lone industrial unit, already set up on its bank. ilike other rivers, the geographical disposition of this Lver attains unique importance as regards its dynamics for 3) availability of natural runoff water from catchment :eas, which becomes very heavy during the monsoon season 3) regular steady availability of tail race water from a /dro—electric power station throughout the yearThe study also aims at arriving at the balancing forces of inherent self~purification of the river verses pollution loads from the factory effluents. The investigation period falls ahead of actual pollution occurrence and so the ambient conditions for a period of nearly one-and-a—half years were investigated, the analyses of which providflz to formulate the inter-relations of parameters varying with seasons. Tracer experiments were carried out which revealed the dispersion and dilution characteristics of the river in the vicinity of effluent outfall. The studv covers the trial—cum-capacity production periods of the factory during which effluents of various strength and quantity were discharged into the river; a few computed values arQ’cjmpgrQdl ... with the observed values. The base data along with the profiles of Oxygen sag equation have been utilized fb develop a mathematical model of the river with regard to its water quality

Influence of Frequent Flyer Programme and Airline Service Quality on Re-buy Intentions of Airline Frequent Passengers

The growth potential of service sector, especially the aviation sector in the Indian economy is splendid. Therefore, it is crucial for the airline service providers to realize their customers, design offers and deliver the desired value to their customers. This study reveals the effect of airline passenger satisfactions particularly on re-buy intentions derived from the attributes-level performance dimensions of both service aspects and loyalty programme of an airline. The mediation effect of satisfaction and other selected antecedents on the re-buy intention of a passenger is hypothesized in this study. Critical areas affecting buying intentions such as core service quality and loyalty attribute-level performances, effect of frequent flyer programme and service quality satisfaction, passenger trust on airline, brand image and moderating effects of perceived value, frequent programme status and travel frequency of airline passengers are linked in a structural model to assess the strength of each facet in affecting re-buy intentions. Implications to the airlines were made based on the finding that re-buy intentions cannot be attributed solely to the impacts of frequent flyer programme, rather affected through the mediation effect of airline service quality satisfaction, which is very much valid for the higher FFP status category of frequent travelers. The effects of moderation caused by perceived value, FFP status and flying experience were also found to be significant in making re-buy intentions.

An Improved Technique for Evolving Wavelet Coefficients for Fingerprint Image Compression

In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16:1. These evolved coefficients perform well for other compression ratios also.

Image Denoising Using Sure-Based Adaptive Thresholding In Directionlet Domain

The standard separable two dimensional wavelet transform has achieved a great success in image denoising applications due to its sparse representation of images. However it fails to capture efficiently the anisotropic geometric structures like edges and contours in images as they intersect too many wavelet basis functions and lead to a non-sparse representation. In this paper a novel de-noising scheme based on multi directional and anisotropic wavelet transform called directionlet is presented. The image denoising in wavelet domain has been extended to the directionlet domain to make the image features to concentrate on fewer coefficients so that more effective thresholding is possible. The image is first segmented and the dominant direction of each segment is identified to make a directional map. Then according to the directional map, the directionlet transform is taken along the dominant direction of the selected segment. The decomposed images with directional energy are used for scale dependent subband adaptive optimal threshold computation based on SURE risk. This threshold is then applied to the sub-bands except the LLL subband. The threshold corrected sub-bands with the unprocessed first sub-band (LLL) are given as input to the inverse directionlet algorithm for getting the de-noised image. Experimental results show that the proposed method outperforms the standard wavelet-based denoising methods in terms of numeric and visual quality

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